COVID-19 modelling numbers are scary. Have we mortgaged our future on an inexact science?

Health-care workers do testing at a drive-thru COVID-19 assessment centre at the Etobicoke General Hospital in Toronto on Tuesday. Officials have asked that people stay inside to help curb the spread of the coronavirus.

The slide on page 13, Dr. Peter Donnelly warned those virtually tuned in to the technical briefing of Ontario’s grim COVID-19 projections late last week, would be the most disturbing of all. Indeed, the number was scary: Without physical distancing measures, Ontario would see 100,000 deaths over the course of the pandemic.

It wasn’t the only shocking figure: The impact of COVID-19 would have been an estimated 300,000 cases and 6,000 deaths by the end of this month alone with no interventions. An estimated 220,000 cases and 4,400 deaths have been spared by sealing off schools, banning large gatherings, shutting non-essential workplaces, closing outdoor rec facilities and, now, ticketing people $880 for walking their dogs through closed parks, according to the models. Another 1,350 deaths (from 1,600 to 250) could be prevented in the coming two weeks with further enforced measures, Donnelly, president and CEO of Public Health Ontario, said Friday.

The range of scenarios seems dizzying, the predictions seriously extreme. Already, critics are insisting the models bias high, leading many to wonder how much we should trust the models upon which so many life-upending decisions are being made.

It’s not possible to be exact about where we will end up … it’s difficult to know exactly where you stand… projections and modelling for a brand new viral disease are very inexact… this is not an exact science.

Donnelly used the word exact, or variations of it, six times throughout the briefing. Yet the imperfect science is informing Ontario’s strategy. And it underlines how assumptions used in modelling the pandemic may rest on “very flimsy foundations,” as Robert Dingwall, a professor of sociology at Britain’s Nottingham Trent University said this week in response to a study questioning the benefits of school closures in terms of scientific evidence.

The Ontario models made projections in terms of mortality based on the global experience thus far of COVID-19, as well as data gathered from Canada. The tables released Friday pegged the case fatality ratio (the percentage of confirmed infections that end in death) at 2.1 per cent overall for Ontario, from 0 per cent for people aged less than 40, to a truly scary 15.9 per cent for people 80 years and over. However, the case fatality ratio is based on known infections, and biases in both directions can inflate or underestimate it — notably, not counting mild cases can produce a falsely high one.

A study published last week in Lancet Infectious Diseases, based on lab-confirmed and clinically diagnosed cases in mainland China as well as international cases, the best estimate of the case fatality ratio was 1.38 per cent overall. The estimate for the overall infection fatality ratio for China (the percentage of people who become infected and die, including those who show no symptoms) was 0.66 per cent.

The virus is extraordinarily efficient at spreading between us, and it’s highly likely almost everyone will get it

Donnelly said the Ontario projections were based on “other things,” though he didn’t elaborate. Officials didn’t release the actual models, just the projections. It’s not clear what variables were plugged in. They were also vague when asked by a reporter from the Globe and Mail about the boundaries for the death projections and how much confidence they have in those boundaries.

Italy is one of the worst impacted countries in the world. On March 1, there were 1,701 confirmed cases in Italy. By April 6, there were 132,547, a nearly 78-fold increase. On April 1, the number of confirmed cases in Ontario was 2,292. “If we apply the same trajectory from Italy, the number of cases would be around 180,000 in Ontario by April 30,” Kristal said.

The trajectory of confirmed cases in Ontario between March 1 and April 1 was 159-fold. “If the same trajectory is applied from April 1 to April 30, as a worst-case scenario, we can reach to 300,000 total confirmed cases.”

Social distancing doesn’t change the likelihood of getting the virus, just the timing. Never before seen in human beings, the virus is extraordinarily efficient at spreading between us, and it’s highly likely almost everyone will get it.

“The question is when, not if. And that’s a crucial question,” said Robert Smith, a disease modelling professor at the University of Ottawa.

The idea behind social distancing is to avoid drowning ICUs. Last week, Ontario released triage guidelines for a major surge in cases. In the worst-case scenario, anyone with a greater than a 30 per cent chance of dying would be denied an ICU bed, and not just COVID-19 patients, but people admitted with cardiac arrest, people with advanced cancer or those with a “frailty score” greater than or equal to 3, meaning only the “very fit” or “well” (people who otherwise have no active underlying diseases, who often exercise or are “very active occasionally”) would get a critical care bed. Those denied admission to an ICU would receive palliative care, including pain and “comfort medications,” according to the document.

The people at highest risk of requiring intubation are also at the highest risk of dying from competing causes, such as heart disease or chronic obstructive pulmonary disease. The 27 deaths in an Ontario nursing home are tragic. But the median survival of nursing home residents at end of life is five months, according to one 2010 study. While seriously disheartening, “It is quite likely that most, if not all of those fatalities would have happened regardless of the COVID-19 epidemic,” said one doctor, who we agreed not to identify “as any dissenters within the medical community are likely to be targeted,” the physician said.

“One has to consider that our health-care system is mortgaging the future prosperity of our youth for an impossible promise of immortality.”

The World Health Organization, however, cautioned last week that young people are becoming critically sick and dying from COVID-19. In Italy, 10 to 15 per cent of all those in ICU are under 50. In Canada as of April 1, the highest proportion of reported cases was among 40- to 59-year-olds (36 per cent), followed by 20 to 39 (29 per cent) and 60 to 79 (25 per cent) though the highest proportion of hospitalizations and ICU admission are among the 60 and older (59 per cent).

“There was a tendency for the last several months, almost a dismissive attitude, to say, ‘Well, this disease is severe in older people, and it’s fine in younger people,” Dr. Mike Ryan, WHO’s director of emergencies program said. “We collectively have been living in a world where we’ve tried to convince ourselves that this disease is mild in young people and more severe in older people, and that’s where the problem is.”

The Ontario models don’t make assumptions about unknown cases. “Let’s be honest and frank,” Donnelly said. “There clearly are many cases in the province that we don’t know about … But again, these models in terms of worst-case projections and in terms of where we now think we are headed are not dependent on that sort of data.”

In the early days of an epidemic, he said, it’s all about providing an important “early steer” to policymakers about what they should be doing. As soon as the government’s “command table” saw the figure that suggested there could be an overall mortality of between 90,000 and 100,000 deaths, they moved quickly to shut schools.

Modelling is good if the data are perfect. But we never have perfect data, and critical information is missing: What’s the transmission rate? What proportion is going to live or die? Can the infected get re-infected? How much are asymptomatic people driving this? The data are changing almost daily. When looking at a time scale of months, it’s like driving through a blizzard.

According to the York analytics, it seems the growth rate in the number of confirmed cases in Canada appears to be slowing down. Epidemiologists are already bracing for the finger-pointing when the attack rates aren’t worst-case, because governments instituted social distancing.

But neither is an almost medieval “just close the door and stay in your house” public health approach feasible in the long term, given the impact on the economy — hundreds of billions of dollars to support the millions who have lost their jobs and businesses — and society at large, Stanford University epidemiologist Dr. John Ioannidis said on a recent Monk Debates podcast.

COVID-19 is a serious threat, he said, but “there’s a lot that we can get wrong if we don’t get it right.”